R: Robust principal component analysis

acprob {amap} | R Documentation

## Robust principal component analysis

### Description

Robust principal component analysis

### Usage

    acprob(x,h,center=TRUE,reduce=TRUE,kernel="gaussien")

### Arguments

`x` | Matrix / data frame
`h` | Scalar: bandwidth of the Kernel
`kernel` | The kernel used. This must be one of '"gaussien"', '"quartic"', '"triweight"', '"epanechikov"' , '"cosinus"' or '"uniform"'
`center` | A logical value indicating whether we center data
`reduce` | A logical value indicating whether we "reduce" data i.e. divide each column by standard deviation

### Details

`acpgen` compute robust pca. i.e. spectral analysis of a robust variance instead of usual variance. Robust variance: see `varrob`

### Value

An object of class acp The object is a list with components:

`sdev` | the standard deviations of the principal components.
`loadings` | the matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors). This is of class `"loadings"`: see `loadings` for its `print` method.
`scores` | if `scores = TRUE`, the scores of the supplied data on the principal components.
`eig` | Eigen values

### Author(s)

Antoine Lucas

### References

H. Caussinus, M. Fekri, S. Hakam and A. Ruiz-Gazen, A monitoring display of multivariate outliers Computational Statistics & Data Analysis, Volume 44, Issues 1-2, 28 October 2003, Pages 237-252

Caussinus, H and Ruiz-Gazen, A. (1993): Projection Pursuit and Generalized Principal Component Analyses, in New Directions in Statistical Data Analysis and Robustness (eds. Morgenthaler et al.), pp. 35-46. Birk\"auser Verlag Basel.

Caussinus, H. and Ruiz-Gazen, A. (1995). Metrics for Finding Typical Structures by Means of Principal Component Analysis. In Data Science and its Applications (eds Y. Escoufier and C. Hayashi), pp. 177-192. Tokyo: Academic Press.

Antoine Lucas and Sylvain Jasson, Using amap and ctc Packages for Huge Clustering, R News, 2006, vol 6, issue 5 pages 58-60.

### See Also

princomp acpgen

[Package amap version 0.8-18 Index]